Manipulator Package Sorting and Placing System Based on Computer Vision

Nowadays the logistics industry is developing rapidly. This paper proposes and designs a vision-based manipulator express sorting and delivery system for the problem of express stacking. This system combines computer vision, deep learning, manipulator control and motion planning technologies. This paper uses the YOLO algorithm and PCL to determine the position and normal vector of the pick-up point of the package, plans and controls the movement of the manipulator to the target position to suck the package, and uses vision to determine the size of the package and obtain customer information. Compared with RCNN and SDD algorithm, YOLO has a faster detection speed [1], and at the same time, it handles small stacked targets such as express boxes with higher accuracy. Therefore, this system uses the YOLOv3 algorithm to improve the system's extraction accuracy and speed. Finally, the success rate of the system was 75%, and the completion time was about 15s.